Technical solutions and innovation are crucial aspects in developing smart, sustainable cities.
But women and men use the city in different ways,
and when we focus more on the technology than on how humans interact with it,
we risk developing smart, but unequal, cities.
Gender has impacted how we build cities for as long as we’ve been building them.
To make sure we’re creating the equal, smart cities of the future we need to ask ourselves:
How can we systematically make visible and challenge gendered power structures,
when we find and implement new, innovative solutions to urban challenges?
A foundation for smart cities is smart urban platforms based on open data.
The purpose is to have free and accessible information to help us in
creating smarter and more efficient services.
To avoid creating one-size-fits all solutions
it’s important to gather gender segregated data.
Through that data we can unlock key insights into the different
life conditions of women and men.
But as we collect more and more data, we also need to keep asking critical questions.
Who gathers the data? Who is inputting data into the system?
What possible discrepancies between data and reality can that create?
Who decides what data is relevant to collect, and what data to base our decisions on?
We also have to keep asking questions when we develop
new, innovative solutions, such as autonomous vehicles in public transportation.
We know today that women and men use public transportation in different ways.
We also know that women feel less safe than men in these environments.
What does it feel like to be in a shared environment, when there’s nobody technically in charge?
If we meet that problem with cameras and alarms, what kind of message does that send to passengers?
How can we make sure routes and protocols are planned with different travel patterns
and different travelers in mind?
There are no set solutions, but if we want to challenge gendered power structures,
we need to make sure we’re asking the right questions.
Where should you be able to charge your electric car?
Whose movements trigger smart street lights?
Who chooses what data to train AI’s with?
Read more at genderedlandscape.umea.se.